Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	14,505
2	New Jersey	11,880
3	Massachusetts	7,740
4	Connecticut	6,894
5	Rhode Island	6,729
6	Louisiana	5,702
7	District of Columbia	5,241
8	Michigan	3,723
9	Delaware	3,672
10	Illinois	3,296
11	Pennsylvania	3,251
12	Maryland	2,938
13	South Dakota	2,426
14	Colorado	2,251
15	Indiana	2,138
16	Georgia	2,093
17	Mississippi	1,921
18	Washington	1,770
19	Iowa	1,619
20	Nebraska	1,500
21	Nevada	1,473
22	Virginia	1,448
23	Florida	1,435
24	Vermont	1,350
25	Ohio	1,333
26	New Hampshire	1,318
27	Tennessee	1,314
28	New Mexico	1,269
29	Alabama	1,267
30	Utah	1,232
31	Missouri	1,112
32	California	1,071
33	Kansas	1,057
34	North Dakota	1,053
35	South Carolina	1,020
36	Idaho	984
37	Wisconsin	976
38	Arkansas	963
39	Kentucky	874
40	Arizona	862
41	Texas	844
42	North Carolina	822
43	Oklahoma	806
44	Maine	736
45	Wyoming	625
46	Minnesota	611
47	West Virginia	571
48	Oregon	534
49	Alaska	460
50	Hawaii	421
51	Montana	416
52	Puerto Rico	409

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Massachusetts	503
2	New York	427
3	Rhode Island	405
4	New Jersey	362
5	District of Columbia	232
6	Connecticut	197
7	Nebraska	185
8	Illinois	175
9	Maryland	164
10	Iowa	142
11	Delaware	128
12	Pennsylvania	126
13	Colorado	120
14	Michigan	108
15	South Dakota	108
16	Indiana	96
17	Mississippi	92
18	Kansas	90
19	Louisiana	89
20	Virginia	82
21	New Mexico	71
22	Georgia	66
23	Tennessee	62
24	Arkansas	57
25	North Dakota	54
26	Utah	51
27	New Hampshire	50
28	Nevada	49
29	Wisconsin	48
30	North Carolina	44
31	Minnesota	42
32	Ohio	41
33	Washington	41
34	Alabama	40
35	California	40
36	Puerto Rico	40
37	Florida	39
38	Kentucky	39
39	Arizona	37
40	Missouri	37
41	South Carolina	31
42	Texas	31
43	Oklahoma	25
44	Maine	20
45	Wyoming	20
46	Oregon	15
47	West Virginia	15
48	Idaho	13
49	Vermont	10
50	Hawaii	2
51	Alaska	1
52	Montana	1

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	853
2	New Jersey	660
3	Connecticut	522
4	Massachusetts	396
5	Louisiana	353
6	Michigan	327
7	District of Columbia	233
8	Rhode Island	202
9	Illinois	148
10	Pennsylvania	143
11	Maryland	131
12	Colorado	116
13	Indiana	116
14	Delaware	115
15	Washington	97
16	Georgia	84
17	Mississippi	74
18	Vermont	73
19	Nevada	66
20	Ohio	60
21	Virginia	51
22	Florida	49
23	Oklahoma	49
24	Kentucky	46
25	Missouri	45
26	Wisconsin	45
27	New Hampshire	44
28	New Mexico	44
29	Alabama	43
30	Minnesota	43
31	California	42
32	Kansas	40
33	Arizona	37
34	Maine	37
35	Iowa	35
36	South Carolina	32
37	Idaho	31
38	North Carolina	28
39	Nebraska	27
40	Tennessee	27
41	Texas	22
42	North Dakota	20
43	Oregon	20
44	West Virginia	18
45	Puerto Rico	16
46	Arkansas	15
47	Montana	13
48	Utah	12
49	Wyoming	12
50	South Dakota	11
51	Alaska	9
52	Hawaii	9

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	New Jersey	30
2	Connecticut	29
3	Massachusetts	26
4	New York	22
5	District of Columbia	17
6	Michigan	15
7	Louisiana	12
8	Rhode Island	10
9	Maryland	9
10	Colorado	8
11	Illinois	8
12	Delaware	7
13	Indiana	6
14	Minnesota	3
15	Mississippi	3
16	New Mexico	3
17	Pennsylvania	3
18	Vermont	3
19	Virginia	3
20	California	2
21	Iowa	2
22	Maine	2
23	Missouri	2
24	Nevada	2
25	New Hampshire	2
26	Ohio	2
27	Oklahoma	2
28	Washington	2
29	Arizona	1
30	Florida	1
31	Georgia	1
32	Kentucky	1
33	Nebraska	1
34	North Carolina	1
35	South Carolina	1
36	Texas	1
37	Wisconsin	1
38	Alabama	0
39	Alaska	0
40	Arkansas	0
41	Hawaii	0
42	Idaho	0
43	Kansas	0
44	Montana	0
45	North Dakota	0
46	Oregon	0
47	Puerto Rico	0
48	South Dakota	0
49	Tennessee	0
50	Utah	0
51	West Virginia	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
New York	New York	95,244	1	99
Lincoln	Arkansas	55,359	2	99
Bledsoe	Tennessee	38,901	3	99
Rockland	New York	34,044	4	99
Marion	Ohio	33,368	5	99
Davidson	Tennessee	3,188	215	93
Richland	South Carolina	1,893	442	85
Pierce	Washington	1,451	589	81
York	South Carolina	630	1272	59
Orange	California	620	1286	59

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
New York	New York	7,011	1	99
Randolph	Georgia	2,803	2	99
Terrell	Georgia	1,993	3	99
Early	Georgia	1,472	4	99
Nassau	New York	1,413	5	99
Pierce	Washington	52	655	79
Richland	South Carolina	43	741	76
Davidson	Tennessee	32	901	71
Orange	California	12	1228	60
York	South Carolina	11	1247	60

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.